Triple
T32120190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BASE jumping |
E820347
|
entity |
| Predicate | isOftenFilmedWith |
P31723
|
FINISHED |
| Object | helmet camera |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: helmet camera | Statement: [BASE jumping, isOftenFilmedWith, helmet camera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOftenFilmedWith Context triple: [BASE jumping, isOftenFilmedWith, helmet camera]
-
A.
alsoFilmedIn
Indicates that the same film or video production was additionally shot or recorded in another specified location.
-
B.
filmedAs
Indicates that an entity was recorded or captured in a particular form, version, or role during a filming or production process.
-
C.
filmedBefore
Indicates that one filming event occurred earlier in time than another filming event.
-
D.
isOftenRecordedWith
chosen
Indicates that one entity is frequently documented, captured, or logged at the same time as another entity.
-
E.
visitedInFilm
Indicates that a location or place is depicted as being visited by a character within the events of a film.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f34902d42c819083a8e6bba9a8bb9a |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c8159edc8190b1c87015e0c820e8 |
completed | May 3, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 12:28 a.m.